EKF-Based Adaptation of Look-Up Tables with an Air Mass-Flow Sensor Application
2011 (English)In: Control Engineering Practice, ISSN 0967-0661, Vol. 19, no 5, 442-453 p.Article in journal (Refereed) Published
A method for bias compensation and online map adaptation using extended Kalman filters isdeveloped. Key properties of the approach include the methods of handling component aging, varyingmeasurement quality including operating-point-dependent reliability and occasional outliers, andoperating-point-dependent model quality. Theoretical results about local and global observability,specifically adapted to the map adaptation problem, are proven. In addition, a method is presented tohandle covariance growth of locally unobservable modes, which is inherent in the map adaptationproblem. The approach is also applicable to the offline calibration of maps, in which case the onlyrequirement of the data is that the entire operating region of the system is covered, i.e., no specialcalibration cycles are required. The approach is applied to a truck engine in which an air mass-flowsensor adaptation map is estimated during a European transient cycle. It is demonstrated that themethod manages to find a map describing the sensor error in the presence of model errors on ameasurement sequence not specifically designed for adaptation. It is also demonstrated that themethod integrates well with traditional engineering tools, allowing prior knowledge about specificmodel errors to be incorporated and handled.
Place, publisher, year, edition, pages
Elsevier , 2011. Vol. 19, no 5, 442-453 p.
Bias compensation, EKF, Parameter estimation, Map adaptation
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-67591DOI: 10.1016/j.conengprac.2011.01.006ISI: 000290744300003OAI: oai:DiVA.org:liu-67591DiVA: diva2:411456